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Novus Examples
json199 B

Inventory Warehouse Locations (JSON)

Warehouse and bin metadata for WMS routing tests.

JSON parsing
Preview, first 15 linesjson
{
  "locations": [
    {
      "id": "WH-EAST",
      "city": "Springfield",
      "bins": 48
    },
    {
      "id": "WH-WEST",
      "city": "Riverton",
      "bins": 32
    }
  ]
}

Specifications

Domain
inventory
Locations
2

Testing contract

Expected to pass
Scenario
Exercise Inventory Warehouse Locations (JSON) in its inventory workflow. Warehouse and bin metadata for WMS routing tests.
Expected result
top-level keys are locations; array lengths: locations=2. Declared feature checks: domain=inventory; locations=2.

What is a .json file?

JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.

How to use this file

Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.

How to use this file for testing

“Inventory Warehouse Locations (JSON)” is a deterministic Novus Examples fixture for JSON parsing. Flat, deeply nested, JSON Lines, and intentionally invalid JSON for testing parsers and error handling.

Documented properties for this file: JSON · 199 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.

Data fixtures document their exact quirks (delimiters, encodings, null handling, schema, and row counts) in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.

Feed the file to your parser and assert it handles the documented quirks, quoted delimiters, embedded newlines, ragged rows, or invalid syntax; the valid↔invalid distinction is labelled in the title.

Code examples

import json

with open("warehouse-locations.json") as f:
    data = json.load(f)
print(type(data), len(data))

Related files

Generated by generation/data_wave_f.py. Free for any use, no attribution required, license.